Latest AI and machine learning research in prostate cancer for healthcare professionals.
INTRODUCTION: We compare the results of modern external-beam radiotherapy (EBRT), using combined androgen deprivation and dose-escalated intensity-modulated radiotherapy with MRI-CT fusion and daily image guidance with fiducial markers (DE-IG-IMRT), with recently published Australian series of brachytherapy and surgery.
Castration-resistant prostate cancer emerges from coupling between cell-intrinsic heterogeneity and microenvironmental constraints. Mechanistically dissecting this coupling, rather than either factor in isolation, is the central aim of this study. To systematically study the effect of intrinsic and extrinsic spatial axes on disease trajectories, we developed an integrated multiscale framework: a c...
Deep learning models for prostate MRI-based cancer grading may encode clinical covariates that either reflect useful disease-related signal or non-gen...
Non-invasive prediction of Gleason Grade Group (GGG) in prostate cancer using multiparametric MRI (mpMRI) is clinically vital for reducing unnecessary...
Objective: To develop and evaluate an Observational Medical Outcomes Partnership (OMOP) standardized prostate cancer database from the University of T...
Abstract Background Prostate cancer (PCa) diagnosis remains challenged by the limited specificity of prostate-specific antigen (PSA) testing, which ca...
Objectives: This study investigates large language models (LLMs) for clinical entity projection across substantial textual transformation. Specificall...
Phylogenetic inference is a common task in molecular and evolutionary biology and has conventionally required a multiple sequence alignment (MSA), a s...
Background: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persisten...
Second generation antiandrogens, such as enzalutamide, are commonly prescribed to treat advanced prostate cancer. However, enzalutamide resistant pros...
Background: Previous recommendations on screening for prostate cancer relied on ongoing trials of screening with prostate-specific antigen (PSA), whic...
Prostate cancer (PCa) is the second most common cancer and cause of cancer death in American men. Existing risk prediction methods have limited accura...
Summary Background Once the treatment starts, early prediction of treatment benefit and its correlation with overall survival (OS) remains challenging...
Objective: To clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surface ar...
Purpose: Castration-resistant prostate cancer (CRPC) is characterized by marked clinical heterogeneity and poor long-term survival, underscoring the n...
Performance degradation due to covariate shift remains a major challenge for deep learning models in medical image segmentation. An open question is w...
Resistance to androgen receptor inhibitors remains a primary challenge in prostate cancer treatment, yet identifying synergistic co-therapies is hinde...
Multimodal remote sensing technology significantly enhances the understanding of surface semantics by integrating heterogeneous data such as optical i...
Proteolysis-targeting chimeras (PROTACs) have garnered significant attention in drug design due to their ability to induce the degradation of the targ...
High-stakes decision-making involves navigating multiple competing objectives with expensive evaluations. For instance, in brachytherapy, clinicians...